1. Field of the Invention
The application relates to a method used in a wireless communication system and related communication device, and more particularly to, a method for performing feedback load reduction in a wireless communication system and related communication device.
2. Description of the Prior Art
Multiple antennas can provide spatial diversity in wireless fading channels to improve the communication quality. On the other hand, multiple antennas can also create (virtually) multiple channels to increase the system throughput. For the downlink broadcast channel employing multiple antennas, it has been shown recently that dirty paper coding (DPC) achieves the capacity. However, the capacity achieving scheme of the downlink multiple-input multiple-output (MIMO) broadcast channel is difficult to derive. In addition, the vector DPC for such a scheme has a high encoding/decoding complexity. Thus, several works resorted to more practical (but suboptimal), space division multiple access (SDMA) based designs. For example, zero-forcing beamforming (ZF-BF) was to achieve the optimal sum rate growth. However, both DPC and ZF schemes require perfect channel state information (CSI) feedback from the users to the base station (BS) to achieve the optimal performance. This may result in high feedback load and is not practical.
In some studies, a model was proposed to analyze the sum rate loss due to imperfect quantized CSI. In the system considered there, each user quantizes the channel vector to one of the N=2^B quantization vectors and feeds back the codebook index to the BS to capture the spatial direction and magnitude of the channel. To reduce the feedback load, orthogonal random beamforming (ORB) can be used. In the ORB, the BS transmits through orthogonal BF vectors to the users, and each user only needs to feedback its received signal-to-interference-plus-noise ratios (SINR) on different orthogonal BF vectors for the purpose of scheduling. The sum rate performance of the ORB may exhibit the same growth rate as the DPC and ZF BF based schemes when the number of users is large.
There are other works that sought to reduce the feedback load at the scheduling stage. For example, a threshold is set such that a user does not need to feedback when its CSI is below the threshold. This method reduces the system feedback load without affecting the scheduling performance much. In another example, multiple thresholds are set, and the scheduler utilizes a polling process to select the best feedback threshold from these multiple thresholds to further reduce the aggregate feedback load. This method, however, incurs delay due to the polling process. In addition, another scheme was proposed to reduce the feedback load of ZF BF systems through a two-stage feedback. In the first stage, each user feeds back the coarsely quantized version of its CSI, and thus the BS has some information to schedule the users. The BS then broadcasts to the scheduled users and the scheduled users will feedback finer CSI to achieve good ZF BF performance. The drawback of this scheme is also the delay due to the second stage feedback.
According to active user's feedback CSI to scheduler (e.g. BS), the scheduler can adjust the modulation and coding scheme to improve the system throughput and schedule users by channel dependent scheduling algorithm to achieve multi-user diversity gain. However, the feedback load is large when the number of active users is large.